Efficacy and Tolerability of Aprepitant for the Prevention of Chemotherapy-Induced Nausea and Vomiting in Patients With Breast Cancer After Moderately Emetogenic Chemotherapy
Bibliographic record
Abstract
PURPOSE: This is the first study in which the NK(1)-receptor antagonist, aprepitant (APR), was evaluated for the prevention of chemotherapy-induced nausea and vomiting (CINV) with moderately emetogenic chemotherapy. PATIENTS AND METHODS: Eligible breast cancer patients were naive to emetogenic chemotherapy and treated with cyclophosphamide +/- doxorubicin or epirubicin. Patients were randomly assigned to either an aprepitant regimen (day 1, APR 125 mg, ondansetron (OND) 8 mg, and dexamethasone 12 mg before chemotherapy and OND 8 mg 8 hours later; days 2 through 3, APR 80 qd) [DOSAGE ERROR CORRECTED] or a control regimen (day 1, OND 8 mg and dexamethasone 20 mg before chemotherapy and OND 8 mg 8 hours later; days 2 through 3, OND 8 mg bid). Data on nausea, vomiting, and use of rescue medication were collected with a self-report diary. The primary efficacy end point was the proportion of patients with complete response, defined as no vomiting and no use of rescue therapy, during 120 hours after initiation of chemotherapy in cycle 1. The secondary end point was the proportion of patients with an average item score higher than 6 of 7 on the Functional Living Index-Emesis questionnaire. RESULTS: Of 866 patients randomized, 857 patients (99%) were assessable. Overall complete response was greater with the aprepitant regimen than with the control regimen (50.8% v 42.5%; P = .015). More patients in the aprepitant group reported minimal or no impact of CINV on daily life (63.5% v 55.6%; P = .019). Both treatments were generally well tolerated. CONCLUSION: The aprepitant regimen was more effective than the control regimen for prevention of CINV in patients receiving both an anthracycline and cyclophosphamide.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".